The Growing Pains of Digital Art History: Issues for the Study of Art Using Computational Methods

Abstract

Digital methodologies that revolve around the study of text have become popular in humanities disciplines such as literature and history. The potential for studying large groups of text automatically through techniques like text mining has meant that Franco Moretti’s “distant reading” has found more and more proponents. Art history, however, presents some unique barriers to uptake in computational techniques, not least the resistance of art historians, who have raised legitimate concerns about the relevance of such techniques. Many so-called “digital art history” projects focus only on formal characteristics while ignoring context, which does not reflect the nature of art historical study in the last 60 years. The technical challenges of using digital methodologies in the study of art and visual culture have limited the potential benefits of such techniques as well: the methodologies used for images are more complex than text recognition and there is simply not enough preexisting data that needs to be sorted in this way.